CRNN | An AutoML for CRNN , you can perform captcha recognition | Computer Vision library

by sun1638650145 Python Version: 2.1.1 License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | CRNN Summary

CRNN is a Python library typically used in Artificial Intelligence, Computer Vision applications. CRNN has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

An AutoML about CRNN, you can use three or four lines of code to recognize the captcha.

Support

Quality

Security

License

Reuse

Support

CRNN has a low active ecosystem.

It has 14 star(s) with 2 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 1 have been closed. On average issues are closed in 5 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of CRNN is 2.1.1

Quality

CRNN has 0 bugs and 22 code smells.

Security

CRNN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

CRNN code analysis shows 0 unresolved vulnerabilities.

There are 4 security hotspots that need review.

License

CRNN is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

CRNN releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 619 lines of code, 32 functions and 10 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed CRNN and discovered the below as its top functions. This is intended to give you an instant insight into CRNN implemented functionality, and help decide if they suit your requirements.

Run the training
Create dataset
Return the character decoder for the given encoder
Return the backbone backbone
Decodes the predictions of the given decoder
Calculate truncation length
Return list of callbacks
Modify label
Extract images from a directory
Return a tuple of label characters
Read images from a dataframe
Split training validation set
Create the CRNN model
Construct CRNN model
Preprocess a single sample
Get a summary summary of images
Load the dataset
Create a character lookup for character lookup

Get all kandi verified functions for this library.

CRNN Key Features

No Key Features are available at this moment for CRNN.

CRNN Examples and Code Snippets

No Code Snippets are available at this moment for CRNN.

Community Discussions

Trending Discussions on CRNN

Custom metrics work with eager execution only

Convert a pth pytorch file to an onnx model

text recognition and restructuring OCR opencv

How to monitor accuracy with CTC loss function and Datasets? (runnable code included)

How to run Neural Network model on Android taking advantage of GPU?

QUESTION

Custom metrics work with eager execution only

Asked 2021-Nov-11 at 13:54

Based on the answer to a question I asked earlier, I'm trying to make custom metrics word_accuracy and char_accuracy work with CRNN-CTC model implementation in tensorflow. It works perfectly fine in the link after running the following lines:

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ANSWER

Answered 2021-Nov-11 at 13:54

You may not like this kind of solution, but you could try changing your calculate_accuracy and decode_batch_predictions functions so that they only use tf operations:

Source https://stackoverflow.com/questions/69920033

QUESTION

Convert a pth pytorch file to an onnx model

Asked 2021-Aug-18 at 10:31

I'm trying to convert a PyTorch model(pth file containing weights) to an onnx file then to a TensorFlow model since I work on TensorFlow. to then fine-tune it. This is my attempt so far. I keep however getting errors.enter image description here I think the problem is that the weights are for a vision transformer. But I haven't figure out what type of model to use to convert it. I'm assuming a CRNN but if there is an easier way I would love to know. PS: I did load the pth file to my drive. the path is correct

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ANSWER

Answered 2021-Aug-18 at 10:31

Thank you all. I'm trying to use the same architecture as the one in the model I think that might work. I'll update if it does.

Source https://stackoverflow.com/questions/68829209

QUESTION

text recognition and restructuring OCR opencv

Asked 2021-Jun-08 at 12:14

Link to original image https://ibb.co/0VC6vkX

I am currently working with an OCR Project. I pre-processed the image, and then applied pre-trained EAST model for text detection.

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ANSWER

Answered 2021-Jun-07 at 07:02

Here's a possible solution that you can try improving on by trying a few things:

by varying Gaussian parameters
by thresholding the blurred image to see if it improves the result

Code:

Source https://stackoverflow.com/questions/67763853

QUESTION

How to monitor accuracy with CTC loss function and Datasets? (runnable code included)

Asked 2021-May-19 at 20:37

I've been trying to speed up training of my CRNN network for optical character recognition, but I can't get the accuracy metric working when using TFRecords and tf.data.Dataset pipelines. I previously used a Keras Sequence and had it working. Here is a complete runnable toy example showing my problem (tested with Tensorflow 2.4.1):

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ANSWER

Answered 2021-May-17 at 09:45

There probably some issue with [accuracy] with tf.data, but I'm not super sure if this is the main cause in your case or if the issue still exits. If I try as follows, it runs anyway without Sequence (with tf.data).

Source https://stackoverflow.com/questions/67506106

QUESTION

How to run Neural Network model on Android taking advantage of GPU?

Asked 2020-May-20 at 11:08

Anyone tried to run object detection or crnn model on Android? I tried to run crnn model (serialized pytorch) but it takes 1s on Huawei P30 lite and 5s on Samsung J4 Core.

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ANSWER

Answered 2020-Apr-24 at 11:41

At the moment it is not possible to run pytorch on am ARM-GPU:

Github Issue

PyTorch Forum

I think the differences in speed result out of the differnten cpu's!

Source https://stackoverflow.com/questions/61407421

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install CRNN

You can download it from GitHub.
You can use CRNN like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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